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Update collections/_posts/2024-10-20-tabular-explainability.md
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Co-authored-by: Nathan Painchaud <23144457+nathanpainchaud@users.noreply.github.com>
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olivier-bernard-creatis and nathanpainchaud authored Oct 29, 2024
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## Teacher/student classification performances

* Comparaison with two standard machine learning methods: LightGBM and XGBoost
* Comparison with two standard machine learning methods: LightGBM and XGBoost
* Conceptual transformer is the student network
* The main goal is not to obtain the most performant model, but rather a comparable model that is better suited for explainability purposes

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